TGTGInsighttelegram intelligenceLIVE / telegram public index
← GitHub Trends

TGINSIGHT SIMILAR POSTS

Find similar content

Source channel @githubtrending · Post #15340 · Dec 17

#python#gym#gym_environment#reinforcement_learning#reinforcement_learning_agent#reinforcement_learning_environments#rl_environment#rl_training NeMo Gym helps you build and run reinforcement‑learning training environments for large language models, letting you develop, test, and collect verified rollouts separately from the training loop and integrate with your preferred RL framework and model endpoints (OpenAI, vLLM, etc.). It includes ready resource servers, datasets, and patterns for multi‑step, multi‑turn, and tool‑using scenarios, runs on a typical dev machine (no GPU required), and is early-stage with evolving APIs and docs. Benefit: you can generate high‑quality, verifiable training data faster and plug it into existing training pipelines to improve model behavior. https://github.com/NVIDIA-NeMo/Gym

Results

1 similar post found

Search: #throughput

当前筛选 #throughput清除筛选
Crypto M - Crypto News

@CryptoM · Post #65085 · 04/10/2026, 10:56 PM

🚀 Offchain Labs Co-Founder Ed Felten on the Future of Layer 2s Amid Ethereum's Mainnet Scaling Offchain Labs co-founder Ed Felten expressed confidence in the continued relevance of layer 2 solutions like Arbitrum, even as Ethereum focuses on scaling its mainnet. According to NS3.AI, Felten highlighted that layer 2s can maintain their competitiveness by providing faster response times, reduced block times, and increased throughput. #OffchainLabs#EdFelten#Layer2#Ethereum#Arbitrum#Scaling#Blockchain#NS3AI#Throughput#ETH#ARB